The social costs of tropical cyclones

Tropical cyclones (TCs) can adversely affect economic development for more than a decade. Yet, these long-term effects are not accounted for in current estimates of the social cost of carbon (SCC), a key metric informing climate policy on the societal costs of greenhouse gas emissions. We here derive temperature-dependent damage functions for 41 TC-affected countries to quantify the country-level SCC induced by the persistent growth effects of damaging TCs. We find that accounting for TC impacts substantially increases the global SCC by more than 20%; median global SCC increases from US$ 173 to US$ 212 per tonne of CO2 under a middle-of-the-road future emission and socioeconomic development scenario. This increase is mainly driven by the strongly TC-affected major greenhouse gas emitting countries India, USA, China, Taiwan, and Japan. This suggests that the benefits of climate policies could currently be substantially underestimated. Adequately accounting for the damages of extreme weather events in policy evaluation may therefore help to prevent a critical lack of climate action.


Supplementary Figures S1-S15
Our data w/ TC-effects  Our data w/o TC-effects  Our main specification  Our main specification w/o TC-effects  Our main specification w/o temp.effects  Fig. S1.Effects of annual average temperature and tropical cyclones (TCs) on economic production for different model configurations.Upper panel: Temperature effect on economic activity (as change in logarithm of per-capita GDP) found for the regression model of Eq. ( 1) with TC effect (solid lines) and without TC effects (dotted lines) for the periods 1961-2010 (orange) and 1981-2015 (green, main specification) as obtained from our data as well as obtained from the data used by Burke et al. in ref. 1 for the period 1961-2010.Shaded areas mark 90% confidence intervals from bootstrapping.Lower panel: Cumulative impact of TCs on economic activity per 1% change in exposed people as a function of the lag years for a maximum number of 8 lag years.Same colour and line codes as in upper panel.In addition the dashed line indicates the regression model without temperature effect.
in exposed people (%) Burke et al. 2015 data w/ TC-effects (1961-2010) Burke et al. 2015 data w/o Fig. S2.Significance of TC-induced growth impacts for different lag numbers.The TCinduced growth impacts are not significant for lag numbers 7 ≤ L ≤ 13 at a 5% level of significance, except for L = 8 and L = 11(top).This means that the cumulative effects remain almost unchanged for higher lag numbers while uncertainty increases (bottom).Based on this, we decided to use L = 8 lags as main specification.

Fig
Fig. S11.Distributions of country-level growth responses to tropical cyclone strikes.Continuation of Fig. S5.

Fig. S14 .
Fig. S14.Country-level temperature-dependent damage functions for tropical cycloneinduced growth losses.The markers denote the 66% confidence range of annual relative growth losses across uncertainty dimensions 2, 4, and 5 (Tbl. 1) for three Representative Concentration Pathways (RCPs 2.6 (blue), 6.0 (orange) and 8.5 (red)).Black (colored) lines and shaded areas denote the fixed (random) effects in the mixed linear model and their 66% confidence intervals, respectively.Continued for other countries in Fig.S13.Parameters: 8 lags and Ricke's discounting choice (main specification).

Growth losses by tropical cyclones
. Average annual growth losses due to tropical cyclones in 1981-2015; note log-scale on x-axis.The quadrants classify countries by above (high) and below (low) median income and losses across the exposed countries for which income data is available.The plot is for the main configuration with 8 lag years.

. Distributions of country-level growth responses to tropical cyclone strikes.
Depictedare the distributions of country-level cumulative growth responses to tropical cyclones from 1,200 bootstraps for 2, 5, 8, 12, 15 lag-years (color code).Vertical lines with circles denote the median growth responses for 0-15 lag years.The order of countries follows the magnitude of the associated impacts from large impacts to small impacts (see x-axis scaling).Continued for other countries in Figs.S6 to S11.

. Distributions of country-level growth responses to tropical cyclone strikes. Contin
for a visualization.